The Best of Its Kind | Introduction to Algorithms | Thomas Cormen, Charles Leiserson, ...

An encyclopedia not a textbook | Introduction to Algorithms | Thomas Cormen, Charles Leiserson, ...

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	• Introduction to Algorithms Thomas Cormen, Charles Leiserson, ... McGraw-Hill Science/Engineering/Math, 2003 - 1056 pages average customer review:based on 167 reviews view larger image
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highly recommended

simply, the best

I'm a graduate Computer Science student.
This book was the most useful while i was in school, and even after i graduated i'm still using it, and it's the best of its kind.

The Best of Its Kind

This is an excellent book but it ought not be your very first
introduction to algorithms. Also, if you have never understood a
mathematical proof, this book isn't for you. In that case, you probably
ought to avoid doing any work that involves implementing (as opposed to
using) complex algorithms. For those who are, or soon will be, deeply
involved in implementing (and creating) algorithms this book is as good
as it gets. It is not, however, the only book you want. Robert
Sedgewick's books titled "Algorithms in ..." come at the subject from a
somewhat more empirical point of view. You need that too. (Not
"instead", but "too".) If you are just getting started and want
a little theory mixed with some challenging problems, look at
"Programming Challenges" by Skiena and Revilla.

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An encyclopedia not a textbook

Frankly I think that this is the most over-hyped CS book on the planet.
Every data structure or algorithm begins with the pseudocode followed by the explanation and analysis. Technically this may be complete, but with this layout it is very difficult to develop an intuitive feel for algorithm design and this is the book's major failure.
The explanation is something like this:
line 12 swaps p[x] and p[y] because ... line 13 is the beginning of the for loop... line 14 calls procedure ....
It seems that all this book does is encyclopedically lists algorithms without bothering to try and train the reader to develop his own, which brings me to its exercises.
The authors seem to be on some sort of ego trip with the complicated exercises and problems offering no solutions or answers to them.
I believe that unless they provide step by step solutions to these problems, no reader particularly the self-learner can grasp algorithm design and learn to write his own.
Most of this book is math, is this book focussed on CS undergrads looking to work in the real world or research scientists? The book is perfect if you are in MIT, but what happens to the average reader?
Having layed down the criticism this book does have its strong points especially its fantastic pseudocode and in depth analysis. I don't think that you would find a more comprehensive book either.
In the end i think that one should buy the book more for its value as a reference rather than hoping to learn something from it.

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This book is for students and academicians

There's always been a confusion about programming and the study of algorithms. This is due to the nature of computer science which lies between the practical world where the professionals reside and the theoretical aspects of computing where (we) students and (our) professors live. So:

1) If you want to learn the theory of algorithms and how to make correctness proofs and how to analyze them, this is the place to start.

2) Every chapter presents non-trivial content accompanied with up to date references at the end. If you are excited in what you have read in a chapter, you can definitely find the more advanced books and articles to pursue your studies accordingly. In this sense, the book is unmatched in its category.

3) If you are a programmer, you have two options:

a) Go, get a simple "Data Structures and Algorithms" book if you are so passionate about seeing actual code in a book. In this way, though you would constrain yourself to a small subset of algorithms and data structures.

b) Try to understand what really an algorithm (or the algorithm you are specifically looking for) is and then code it yourself with the help of this book. I admit that the treatment of the material is not in a way to permit this easily. But, the figures may help.

4) The authors falsely states that this book is "also" for professionals. This is obvious.

5) The book lacks some solid background material to analyze the algorithms. Though, this would make it a 1500 page huge tome.

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